Qin shi huang cannabis seeds

Beyond our common impressions of terra cotta

For centuries humans have used terra cotta to craft art, preserve history and hold plant life.The most commonly known historical use of terra cotta dates back to 246 BC, when the Chinese emperor Qin Shi Huang used the material to create a Terracotta Army to protect himself in the afterlife. The oldest known use of terra cotta has been traced as far back as 26,000 BCE during the paleolithic era, when ancient humans used the clay to create female figurines. European traders would use terra cotta vessels to transport valuable spices, agricultural plants and other rare plant specimens across trading routes.

Today, experienced artisans continue to work the wet clay at a pottery wheel to create beautiful vases, pots and works of art. While terra cotta pots look beautiful in their natural rosy red color, they can easily be decorated with vibrant colored glazes. Choosing planting containers made from terra cotta over plastic and fiberglass materials is an eco-friendly option for your indoor and outdoor plants.

The natural earthenware of terra cotta is a healthy container of choice for your potted plants. When terra cotta is fired at low temperatures the minerals are only partially melted creating a porous texture. The porous texture is ideal for allowing air and moisture to exchange through the pot, reducing the risk of soil diseases and root rot. This can be especially helpful if you live in an area with a colder climate. However, evaporating moisture also means that roots may dry out more easily. Plants that prefer dry soil won’t mind, making terra cotta pots an ideal home for cacti and succulents. If your plant prefers to stay moist you may have to water it more frequently. Always check the moisture levels of your plants to keep them in optimal health.

The image of a terra cotta pot brings back memories of warm days when the sun heats the clay and soil of potted plants in the garden. Terra cotta is an Italian word meaning “baked earth” and refers to any type of porous clay that is fired in a kiln at low temperatures or baked in the sun. A garden filled with terra cotta pots will be decorated with the traditional reddish brown color of iron oxides in the clay. The natural minerals in terra cotta oxidize with exposure to the air to form what are called patinas, the colorful swirls of orange and pink mineral deposits. This character gives this earthenware a much desired rustic look.

Transcriptome differences between fiber-type and seed-type Cannabis sativa variety exposed to salinity

The industrial hemp varieties ‘Yunma 5’ and ‘Bamahuoma,’ which demonstrate growth vigor and environmental adaptability, have been primarily cultivated in Yunnan and Guangxi, China, respectively, for fiber and seeds. The results of physiological measurements showed the phenotypic differences between the two varieties in response to salt stress. RNA-Seq analysis was first performed on leaves of both varieties sampled at four time intervals (0, 2, 4, 6 days) after treatment with salt (500 mM NaCl) We identified 220 co-up-regulated differentially expressed genes (DEGs) in the two varieties, while 26 up-regulated DEGs and 24 down-regulated DEGs were identified exclusively in the single varieties after 2 days of salt stress. Among the 220 DEGs, we identified 22 transcription factors, including key transcription factors involved in salt stress, such as MYB, NAC, GATA, and HSF. We applied gene expression profile analysis and found that ‘Yunma 5’ and ‘Bamahuoma’ have variety-specific pathways for resisting salt stress. The DEGs of ‘Yunma 5’ were enriched in spliceosome and amino acid metabolism genes, while the DEGs of ‘Bamahuoma’ were enriched in fatty acid metabolism, amino acid metabolism, and endoplasmic reticulum protein processing pathway. Although there were common DEGs, such as genes encoding cysteine protease and alpha/beta-hydrolase superfamily, the two varieties’ responses to salt stress impacted different metabolic pathways. The DEGs that were co-expressed in both varieties under stress may provide useful insights into the tolerance of cultivated hemp and other bast fiber crops to saline soil conditions. These transcriptomes also represent reference sequences for industrial hemp.

Electronic supplementary material

The online version of this article (doi:10.1007/s12298-016-0381-z) contains supplementary material, which is available to authorized users.

Introduction

Soil salinization is a growing global problem due to environmental deterioration caused, especially in China, by a shortage of cultivated land (Li et al. 2014). Salt stress in plants causes cell dehydration, osmotic stress, the generation of reactive oxygen species (ROS), and lack of absorption of the nutrient K + due to Na + competition (Ren et al. 2005). Salt stress also influences electron transfer, carbon assimilation, and light absorption and conversion due to the closure of stomata, slowing down or even halting growth in crop plants (Mao et al. 2008). Although salt stress can cause great harm to plants, salt damage can be tolerated by plants to a certain extent through various mechanisms, such as hormone regulation, ion transport, induction of antioxidant enzymes, and K + /Na + homeostasis regulation. Therefore, research on crop salt tolerance has important implications for agricultural production.

Hemp (Cannabis sativa) has been cultivated in China for thousands of years. C. sativa is an annual dioecious herbaceous species evolved from wild Cannabis (Cannabaceae) varieties (Yang 2003; Sun 1993). Industrial hemp contains less than 0.3 % of the psychoactive cannabinoid Δ 9 -tetrahydrocannabinol (THC) in the young leaves and flowers. Industrial hemp is grown for its fibers to be used as raw materials in making paper, textiles, and biocomposite products (Struik et al. 2000). Hemp seeds are rich in oleic acid, linoleic acid, and other polyunsaturated fatty acids essential to humans. Industrial hemp also has important medical value, including anti-inflammatory, analgesic and anti-seizure roles of cannabinol (CBN), which is extracted from hemp leaves (Dai 1989). Due to increased shortages of cultivated land and the vast amounts of salinated land in China, it is necessary to improve the growth of bast fiber crops in salinated soil. ‘Yunma No.5’ and ‘Bamahuoma’ are two distinct industrial hemp varieties for different uses in China. ‘Bamahuoma’ has cultivated in Guangxi Province for the seed production. ‘Yunma 5’ is one of the most important industrial hemp varieties and is grown in Yunnan Province for fiber production. We hypothesized that these two varieties have diverged from each other due to their adaptions to different growth environments, resulting in distinct regulatory and metabolic pathways under salt stress. In order to verify our hypothesis, RNA-Seq was first performed on the leaves from the seedlings of these two varieties exposed to high salinity during early developmental stage. All genes were compared with the available reference C. sativa sequence (Bakel et al. 2011). Our results would be helpful in further studies on salt resistance mechanisms in bast fiber crops. Differentially expressed salt-regulated genes in the two hemp varieties could also be used in breeding programs to improve the salt resistance of these crops.

Materials and methods

Plant materials and NaCl treatment

The plant materials of ‘Yunma 5’and ‘Bamahuoma’ were provided by Yunnan Academy of Agricultural Sciences and Guangxi Academy of Agricultural Sciences respectively. The seeds of two varieties were planted in the pots of 19 cm in height and 16 cm with an equivalent weight matrix (peat and perlite mixed in 1:1 ratio). Every variety has 18 pots: 9 pots for control; 9 pots for salt treatment. The salt treatment was applied when seedlings had 3–4 pairs of true leaves (about 15–20 cm high). The pots for salt treatment were watered with 400 ml of 500 mM NaCl once, while the pots for control watered with 400 ml plain water. All pots were watered with 400 ml plain water every two days after salt treatment to supple evaporated water. The leaves in three pots per treatment of one variety were randomly sampled at four time intervals (treated for 0, 2, 4 and 6 days) and stored at −80 °C for measurement of physiological parameters and total RNA extraction.

Measurement of physiological parameters

In this study, we assessed physiological parameters to evaluate the tolerance of the hemp varieties ‘Yunma 5’ and ‘Bamahuoma’ to a high concentration of NaCl (500 mM). After harvesting 3–4 pairs of true leaves from seedlings irrigated with 500 mM NaCl, the degree of salt tolerance of the two varieties was evaluated through measurements of the relative electrical conductivity (REC) and the free proline content.

Relative electrical conductivity (REC)

Sampled leaves (0.1 g) were cut into similar sized pieces and were soaked in capped tubes with 10 ml distilled water for 12 h at room temperature. The initial electrical conductivity of the extracting solution (R1) was tested using a DDS-306 electrical conductivity meter (Fangzhou Company, Chengdu, China). The solutions were then heated to 100 °C for 30 min and subsequently cooled to room temperature; the final electrical conductivity was measured (R2). The REC was calculated as follows:

Free proline content

The concentration of proline in control and salt-treated seedlings were measured following the method of Bates (Bates et al. 1973). The proline agent, extracted with toluene, was measured using a UV-1600 spectrophotometer (Ruili Company, Shanghai, China) at 520 nm. The concentration of proline was estimated using the standard curve prepared from l -proline (0–100 μg/ml). Proline concentration was measured as μg/g fresh weight of sample.

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Total RNA extraction

In order to avoid variability between plant samples, we pooled leaves of three plants randomly selected from one pot to extract total RNA. The total RNA from three pots were mixed together as a single biological replicate. 8 total RNA samples obtained from two varieties for four time intervals. Total RNA was extracted using the TriZol up kit (TransGen Biotech, China) and dissolving into RNase-free water (TransGen Biotech, China). RNA degradation and contamination were inspected on 1 % agarose gels. The RNA was checked for quantity and quality spectrophotometrically at OD260/OD280 ratio. (NanoDrop 2000/2000C Spectrophotometer, Thermo Scientific, USA).

cDNA library construction for RNA-Seq

A total of 8 libraries were constructed and sequenced using the Illumina sequencing platform (Illumina HiSeq™ 2000) by Genedenovo Co.Ltd, Guangzhou, China. Raw reads were filtered by removing low quality sequences to obtain clean reads, on which all subsequent analyses were based.

Identification of DEGs in the two varieties under salt stress

Sequencing reads were mapped to the C. sativa Purple Kush reference genome with BWA (Burrows-Wheeler Alignment Tool, http://bio-bwa.sourceforge.net/bwa.shtml) to obtain the expression levels of all genes. Read counts were analyzed using the bioconductor software package edgeR for analysis of DGE in the statistical environment R (Robinson et al. 2010).

Gene expression level was measured using the number of uniquely mapped reads per kilo base of exon sequence per million mapped reads (RPKM). The false discovery rate (FDR) was used to determine the P value threshold taking into account the multiple tests. Gene expression differences were considered significant with an FDR ≤ 0.001 and an absolute value of the log2 ratio ≥ 1. Hierarchical cluster analysis was conducted using software MeV (MultiExperiment Viewer) based on log2FC ratio value for each DEG.

GO annotation and KEGG pathway of DEGs

To determine biological functions and functional classifications, DEGs were annotated with the Gene Ontology (GO) database (http://www.geneontology.org/) using Blast2GO (Conesa et al. 2005) followed by WEGO software (Ye et al. 2006) to obtain GO functional classifications for all the DEGs. All DGEs were mapped to the Kyoto Encyclopedia of Genes and Genome (KEGG) Pathways database using BLASTX.

Gene expression pattern analysis in two varieties under salt stress

The expression patterns of all DEGs were discovered using STEM (Short Time-series Expression Miner, v1.3.8). Genes were clustered according to their different expression patterns according to variations in time. DE genes belong to the same cluster had similar expression pattern with each other. Clusters with specific expression patterns were selected and verified.

Verification of DEG expression with quantitative real-time PCR

In order to verify the reliability of RNA-Seq, 13 selected candidate DEGs involved in salt stress in both ‘Yunma 5’ (Y5) and ‘Bamahuoma’ (BM) were verified by qRT-PCR. These 13 genes contained 2 genes that were co-up-regulated in the two varieties and 6 and 5 genes up-regulated or down-regulated exclusively in single variety. The functions of the 13 DEGs are shown in Appendix E. First-strand cDNA was synthesized from 0.5 μg of total RNA treated with genomic DNA remover using TransScrip All-in-One First-Strand cDNA Synthesis SuperMix (TransGen, China). Eighteen pairs of primers were designed using Primer-BLAST (http://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi). Primer sequences for the qRT-PCR assay are listed in Appendix A. Real-time PCR was performed on ABI Prism7500 (Applied Biosystems, USA) with 1μL of the first-strand cDNA template that was diluted tenfold. PCR was performed in triplicate to exclude sampling errors using SYBR Green Master Mix under the following conditions: 30 s at 94 °C, followed by 40 cycles of 94 °C for 5 s and 58 °C for 30 s. A quantification method (2 −ΔΔCT ) was used to determine the relative expression levels of 13 DEGs from the two varieties.

Results

Effects of salt stress on physiological parameters

The effects of high salinity on electrical conductivity ‘Yunma 5’ and ‘Bamahuoma’ is shown in Fig. 1 a. Before salt stress (0 day, there was a slight difference in REC between the two varieties. After 2 days, the REC of the ‘Bamahuoma’ variety (75 %) was significantly higher than that of ‘Yunma 5’ (60 %). After 6 days, the RECs of the two varieties had increased to 85 % and 80 %, respectively. The variation in REC was greater for ‘Bamahuoma’ than for ‘Yunma 5’ throughout the duration of salt stress.

Determination of physiological indexes. The relative electrical conductivity (a) and proline contents (b) of ‘Yunma 5’ (Y5) and ‘Bamahuoma’ (BM)

The results of the proline content assessment revealed a significant effect of high salinity on the free proline content in the cells of the two varieties (Fig. 1 b). Salt stress caused a clear increase in proline content in the first 2 days in both varieties. For example, the proline content of ‘Yunma 5’ increased from 375 µg/g at 0 day to 715 µg/g at 2 days. The two varieties, however, showed some significant differences. The proline content of both varieties decreased from 2 to 4 days, but there was a greater reduction in ‘Bamahuoma’, which demonstrated a lower level of proline over days 4–6.

Mapping of reads

After removing low-quality sequences (Q-value <20), adaptor sequences, and reads with more than 50 % N bases, we obtained more than 28 million clean reads from each of the eight cDNA libraries (Table 1 ) and mapped gene expression profiles to the C. sativa genome with match rates of 55.26–67.95 %. Most of these represented unique matches, with the remainder (3.46–5.16 %) being non-unique, multiple-position matches. For further analyses, we only used unique matches.

Table 1

Statistics for Illumina reads mapped to the Cannabis sativa genome

Sample Total clean reads Unique matches (%) Non-unique matches (%) Unmapped reads (%)
Y5C (0 day) 28815872 18187183 (63.12) 1120488 (3.89) 9508201 (33.00)
Y5 (2 days) 34507230 23446718 (67.95) 1780043 (5.16) 9280469 (26.89)
Y5 (4 days) 34998280 21626809 (61.79) 1511467 (4.32) 11860004 (33.89)
Y5 (6 days) 34573380 22510844 (65.11) 1385184 (4.01) 10677280 (30.88)
BMC (0 day) 33652134 18597157 (55.26) 1165299 (3.46) 13889678 (41.27)
BM (2 days) 32591506 18327830 (56.23) 1468316 (4.51) 12795360 (39.26)
BM (4 days) 31423636 19192253 (61.08) 1422049 (4.53) 10809334 (34.40)
BM (6 days) 34276778 19846970 (57.90) 1492242 (4.35) 12937566 (37.74)

Y5C, ‘Yunma 5’ control plants; Y5(2, 4, 6 days), ‘Yunma 5’ salt-stressed plants for 2, 4, 6 days; BMC, ‘Bamahuoma’ control plants; BM(2, 4, 6 days), ‘Bamahuoma’ salt-stressed plants for 2, 4, 6 days

Scatter plots of the abundances of transcripts in control and salt-treated libraries showed that ‘Bamahuoma’ exhibited more DEGs at 2 and 4 days than ‘Yunma 5’ (Fig. 2 ). The scatter plots also showed that the most up-regulated DEGs occurred 2 days after exposure to salt stress that was consistent with the results of physiological parameters. These results were consistent with the results of physiological parameters measurements.

Scatter plots of the abundances of transcripts in control and salt-treated libraries. ac Control versus salt-treated samples of ‘Yunma 5’ (Y5) at 2, 4, and 6 days. df Control versus salt-treated samples of ‘Bamahuoma’ (BM) at 2, 4, and 6 days

DEGs in both varieties under salt stress

To compare DEGs between the salt-stressed and control samples, we selected DEGs whose expression met the following criteria: RPKM > 1, log2FC > 2 and P value

Venn diagrams for the number of differentially expressed genes (a) in ‘Yunma 5’ (Y5) and (b) in ‘Bamahuoma’ (BM) under salt stress for 2, 4, and 6 days, compared to controls (Y5C and BMC)

The DEGs that occurred at 2 days could be classified into eight clusters according to their expression patterns (Fig. 4 ). As these clusters show, 1883 and 282 DEGs were up-regulated in ‘Bamahouma’ and ‘Yunma 5’, respectively, and among these, 220 DEGs were co-up-regulated and 249 were co-down-regulated in the two varieties. Similarly, 2991 and 528 DEGs were down-regulated in ‘Bamahouma’ and ‘Yunma 5’, respectively, including 24 DEGs that were co-down-regulated in the two varieties. There were also 26 DEGs that were up-regulated in ‘Yunma 5’ but down-regulated in ‘Bamahuoma’. In contrast, 24 were up-regulated in ‘Bamahuoma’ but down-regulated in ‘Yunma 5’. The functions of the 220 co-up-regulated genes, the 249 co-down-regulated genes, the 26 genes up-regulated in ‘Yunma 5’ but down-regulated in ‘Bamahuoma’, and the 24 genes up-regulated in ‘Bamahuoma’ but down-regulated in ‘Yunma 5’ are listed in Appendix B.

Number of DEGs in ‘Yunma 5’ (Y5) and ‘Bamahuoma’ (BM) at 2 days. DEGs that were up-regulated or down-regulated exclusively in single variety are shown in each independent circle. DEGs with the same or opposite expression patterns between the two varieties are shown in the overlapping regions

118 salt-responsive DEGs were selected from the four clusters (220 co-up regulated, 249 co-down regulated, 24 and 26 up-regulated and down-regulated exclusively in single variety) in Fig. 4 showed differences between ‘Yunma 5’ and ‘Bamahuoma’. These 118 DEGs and their expression patterns are listed in Appendix I. The 118 DEGs, including 47 co-up-regulated, 60 co-up-regulated, 5 and 8 up-regulated and down-regulated exclusively in a single variety, compared to control in two varieties were classified using hierarchical cluster (Fig. 5 ).

Hierarchical clustering of 118 DEGs related to salt stress at 2 days. Y5-2d, ‘Yunma 5’; BM-2d, ‘Bamahuoma’

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According to KEGG classification, the common clusters in ‘Yunma 5’ (Table 2 ) and ‘Bamahuoma’ (Table 3 ) include ‘Photosynthesis’ and “Photosynthesis – antenna proteins”, the variety-specific clusters are: “Inositol phosphate metabolism”, “Spliceosome” and “Other types of O-glycan biosynthesis” in ‘Yunma 5’, “Porphyrin and chlorophyll metabolism”, “Fructose and mannose metabolism” and “Plant hormone signal transduction” in ‘Bamahuoma’ were significantly enriched metabolic pathways (P < 0.01).

Table 2

KEGG classification for ‘Yunma 5’ at 2 days under salt stress

Pathway DEGs with pathway annotation (1927) All genes with pathway annotation (10351) P value
Y
Photosynthesis 53 (2.75 %) 86 (0.83 %) 1.10497E−18
Photosynthesis – antenna proteins 21 (1.09 %) 30 (0.29 %) 1.06844E−09
Inositol phosphate metabolism 31 (1.61 %) 95 (0.92 %) 0.000734443
Spliceosome 80 (4.15 %) 310 (2.99 %) 0.000929217
Other types of O-glycan biosynthesis 4 (0.21 %) 5 (0.05 %) 0.005099866

Table 3

KEGG classification for ‘Bamahuoma’ at 2 days under salt stress

Pathway DEGs with pathway annotation (1927) All genes with pathway annotation (10351) P value
B
Photosynthesis 66 (2.08 %) 86 (0.83 %) 1.27395E−18
Photosynthesis – antenna proteins 24 (0.76 %) 30 (0.29 %) 3.35059E−08
Porphyrin and chlorophyll metabolism 34 (1.07 %) 72 (0.7 %) 0.00225854
Fructose and mannose metabolism 29 (0.91 %) 62 (0.6 %) 0.005457017
Plant hormone signal transduction 106 (3.34 %) 282 (2.72 %) 0.007034509

Co-expressed transporter-encoding genes and transcription factors in the two variety under salt stress

On the basis of annotation on the Plant Transcription Factor Database (http://planttfdb.cbi.pku.edu.cn/) (Saier et al. 2006, 2009), a number of co-expressed genes differentially regulated in ‘Yunma 5’ and ‘Bamahuoma’ during salt stress were categorized as transporters. The majority of the transporter genes belonged to ion and amino acid transmembrane transporter activity, anion channel activity and transferase (Fig. 6 a, b). A sodium transporter hkt1-like protein homolog, PK17182.1 was found only in ‘Yunma 5’ while another DEG, PK06358.1, a homolog of K + uptake transporter 3 isoform 1 in Theobroma cacao, was found only in ‘Bamahuoma’.

Classification of transcription factor and transporter gene. Distribution of transcription factor gene families in ‘Yunma 5’ (a) and ‘Bamahuoma’ (b). Distribution of transporter gene families in ‘Yunma 5’ (c) and ‘Bamahuoma’ (d)

By searching on the Plant Transcription Factor Database v3.0 (PlantTFDB 3.0) (Jin et al. 2014), 84 and 130 co-expressed genes were differentially regulated in ‘Yunma 5’ and ‘Bamahuoma’ respectively during salt stress. The 84 transcription factors in ‘Yunma 5’ were categorized to 25 compared to the 130 transcription factors in ‘Bamahuoma’ were categorized to 39 transcription factor families (Fig. 6 c, d). Differentially expressed TFs mostly classified to NAC, MYB, WRKY families in these two varieties during salt stress. The transcripts present in each transcription factor family are presented in supplementary data J and K (Fig. 7 ).

Hierarchical clustering of 22 transcription factors among the co-up-regulated DEGs classified into 14 families

The co-up-regulated DEGs at 2 days in the two variety under salt stress

Among the 220 DEGs at 2 days that were co-up-regulated in the two varieties, a few important ones are listed in Table 2 , such as ERF (ethylene response factor) (Zhai et al. 2013; Li et al. 2013; Dong et al. 2012), UDP-glucosyltransferase activity (Lin et al. 2008), alpha/beta-hydrolase superfamily protein (Lenfant et al. 2013), ABC transporter B family member, calcium-dependent lipid-binding family protein isoform 2, cysteine protease, heat shock protein 70, proline-rich cell wall protein-like precursor (Stein et al. 2011), and galactinol synthase 2-like (Sun et al. 2013) (Table 4 ). Four genes, namely the gibberellin receptor 1b, SAUR-like auxin-responsive protein family, histidine kinase 4-like, and GATA domain class transcription factor, are involved in plant hormone signal transduction (Legay et al. 2009).

Table 4

Salt-regulated DEGs that are co-up-regulated in the two varieties

Gene ID Gene annotation RPKM log2 Ratio log2 Ratio
Y5C Y5S BMC BMS (Y5S/Y5S) (BMS/BMC)
PK21644.1 Alpha/beta-Hydrolases superfamily protein (Arabidopsis thaliana) 2.7 21.87 1.72 4.07 2.77 5.98
PK28100.1 Alpha/beta-Hydrolases superfamily protein (Arabidopsis thaliana) 4.85 20.38 3.28 83 2.91 4.67
PK01237.6 Multidrug resistance protein ABC transporter family 17.95 122.41 9.79 257.23 3.02 4.72
PK00363.1 ABC transporter B family member 19-like 2.78 20.67 4.7 66.08 2.07 3.81
PK23459.1 UDP-glucosyltransferase activity 12 56.09 8.39 41.4 2.23 2.3
PK25200.1 UDP- d -glucose/UDP- d -galactose 4-epimerase 5 isoform 1 54.42 241.26 25.89 681.61 2.15 4.72
PK13470.1 Ethylene response factor ERF1 11.12 84 5.81 73.48 2.92 3.67
PK25561.1 Tyrosine metabolism 47.33 211.83 44.89 656.2 2.16 3.87
PK14938.1 Amino acid permease 6 12.3 125.26 26.5 432.76 3.35 4.03
PK25561.1 Aspartate aminotransferase 47.335 211.83 44.89 656.21 2.16 3.87
PK26287.1 Beta-galactosidase 3 isoform 4 2.32 18.24 44.89 656.2 2.98 3.87
PK05306.1 Calcium-binding EF-hand family protein 9.73 86.86 21.8 125.71 3.16 2.53
PK09339.1 Calcium-dependent lipid-binding family protein isoform 2, partial 5.71 26.48 6.37 28.75 2.21 2.18
PK16090.1 Calcium-dependent lipid-binding family protein isoform 4 2.8 22.87 3.63 23.36 3.03 2.69
PK13478.1 Calcium-dependent lipid-binding family protein isoform 4 3.59 24.04 5.18 23.98 2.75 2.21
PK16995.1 Calcium-dependent lipid-binding family protein isoform 4 2.7 14.96 3.2 17.6 2.47 2.46
PK16932.3 Cysteine protease 42.47 558.6 107.54 652.97 3.72 2.6
PK16932.2 Cysteine protease 43.07 378.16 83.35 410.58 3.13 2.3
PK09922.1 E3 ubiquitin-protein ligase RNF25 38.02 155.93 19.84 80.09 2.04 2.01
PK00197.1 Glutamate dehydrogenase 2 8.93 77.95 4.98 230.55 3.13 5.54
PK19568.2 Heat shock cognate 70 kDa protein 1 4.26 20.17 5 178.91 2.24 5.16
PK02428.1 Heat shock factor 4 5.57 26.98 1.92 55.59 2.28 4.85
PK06896.7 Heat shock protein 70 2.12 11.16 1.66 604.38 2.4 8.51
PK28308.1 Heat shock protein 81.4 10.47 121.17 19.54 788.9 3.53 5.34
PK04256.2 Leucine-rich repeat protein kinase family protein isoform 1 1.84 9.578 1.46 67.01 2.39 5.52
PK08070.1 Proline-rich cell wall protein-like precursor 3.62 58.973 17.48 86.67 4.03 2.31
PK15022.1 Aldehyde dehydrogenase family 7 member A1-like Fatty acid metabolism 43.31 387.36 51.81 788.55 3.16 3.93
PK12124.1 E3 ubiquitin-protein ligase RMA1H1-like 6.93 50.36 4.06 142.94 2.86 5.14
PK20686.1 E3 ubiquitin-protein ligase UPL1-like 4.91 38.58 4.29 17.68 2.98 2.04
PK07006.1 Gibberellin receptor 1b 13.45 128.84 3.35 411.16 3.26 6.94
PK17887.1 SAUR-like auxin-responsive protein family 1.02 5.01 1.29 14.55 2.30 3.50
PK02363.1 Histidine kinase 4-like 3.38 17.14 1.57 48.38 2.34 4.95
PK07593.1 GATA domain class transcription factor 20.34 107.90 15.68 79.19 2.41 2.34

Y5C, ‘Yunma 5’ control plants; Y5S, ‘Yunma 5’ salt-stressed plants; BMC, ‘Bamahuoma’ control plants; BMS, ‘Bamahuoma’ salt-stressed plants

RPKM reads per kilobase of exon model per million mapped reads, which was used to represent the gene’s expression level in one tissue

Transcription factors co-expressed in both varieties under salt stress

22 transcription factors at 2 days were identified and classified into 14 families as MYB, NAC, GATA, and HSF based on the Plant Transcription Factor Database (http://planttfdb.cbi.pku.edu.cn/) and their annotations. Among the 22 transcription factors, 7 were co-up-regulated, 7 were co-down-regulated in the two varieties, and 2 were down-regulated in ‘Yunma 5’ but up-regulated in ‘Bamahuoma’. A heat shock factor gene (PK02428.1) exhibited the most significant up-regulated expression profile in ‘Bamahuoma’ (Fig. 8 ). A MYB gene (PK24260.1) exhibited opposite expression patterns in the two varieties, while two other MYB genes (PK06396.1 and PK05123.1) demonstrated similar expression patterns (Fig. 9 ).

Gene expression patterns and GO enrichment analysis of DEGs in profile 16 of ‘Yunma 5’ (a) and profile 14 of ‘Bamahuoma’ (b)

qRT-PCR validation of 13 DEGs. Expression changes of 13 genes in the two varieties at 2 days under salt stress compared to controls was measured by qRT-PCR and compared to RNA-Seq data. Y5C/Y5S = Y5 control sample/Y5 salt-stressed sample; BMC/BMS = BM control sample/BM salt-stressed sample

Gene expression pattern analysis in two varieties under salt stress

Genes were clustered by software STEM according to their different expressions among sequential variations of time (Ernst et al. 2005; Lu et al. 2014) (Fig. 8 ). The four break points in each curve represent the four salt-stress time intervals (0, 2, 4 and 6 days). Based on this analysis, the profiles of genes that were up-regulated and then down-regulated (P ≤ 0.05) were grouped into profile 16 for ‘Yunma 5’ and profile 14 for ‘Bamahuoma’ (Fig. 8 A-B), including 1714 DEGs in Y5 profile 16 and 2509 DEGs in BM profile 14. The DEGs in profile 16 were highly expressed at 2–4 days, while the DEGs in profile 14 were highly expressed only at 2 days.

Genes in these two profiles were subjected to GO-term analysis (Fig. 8 ), which identified electron carrier activity only in ‘Bamahuoma’. Further, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.kegg.jp/kegg/pathway.html) was used to assess the biological functions of the DEGs. Most genes clustered in the two profiles were significantly enriched in metabolic pathways according to the KEGG annotation (P ≤ 0.01). The DEGs in profile 16 of ‘Yunma 5’ were enriched in the spliceosome and cysteine and methionine metabolism pathways (Appendix C). The profile also included six genes denoted HSP70-like protein (PK19568.2, PK06896.7, PK06896.9, PK06896.1, PK06896.2, PK06896.6) that are involved in the MAPK signaling pathway (Zeng and Zhang 2006). Zinc finger family genes (PK07293.1, PK00562.1), which are involved in making rice plants more resistant to salt stress, were also identified (Wang et al. 2015). A 1-aminocyclopropane-1-carboxylate oxidase gene (PK26770.1) involved in cysteine and methionine metabolism also changed its expression in response to salt stress (Pan and Lou 2008).

The DEGs in profile 14 of ‘Bamahuoma’ were enriched in fatty acid metabolism, amino acid metabolism, protein processing, peroxisome, and plant-pathogen interactions (Appendix D). Several genes were involved in fatty acid metabolism, such as lipoxygenase genes (PK00878.1, PK20949.1, PK08197.4, PK12808.1, PK08197.1, PK08197.2, and PK08197.3), aldehyde dehydrogenase family genes (PK00013.1 and PK15022.1), acyl-CoA oxidase genes (PK18899.1, PK09506.1, PK26277.1, PK10458.1, and PK10458.2) and peroxisomal 3-ketoacyl-CoA thiolase genes (PK02646.1 and PK05121.3). The seven lipoxygenase genes are involved, in particular, in alpha-linolenic acid metabolism, while the two peroxisomal 3-ketoacyl-CoA thiolase genes are also involved in leucine and isoleucine metabolism. The KEGG analysis of stage-specific genes suggests that the two varieties’ adaptation to salinity was controlled by different molecular regulatory mechanisms.

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Confirmation of candidate genes expression patterns by qRT-PCR analysis

Results of the qRT-PCR showed that the main trends in the expression of the 13 genes were identical to those identified with RNA-Seq (Fig. 8 ), supporting the reliability of the RNA-Seq data. Moreover, the fold-changes of the 13 genes obtained by RNA-Seq were generally higher than those obtained by qRT-PCR.

Discussion

Few studies have been performed on transcriptional profiling of Cannabis sativa under salt stress. In this study, using a combination of physiological parameters, we investigated the differential expression genes and related pathways of two Cannabis sativa varieties from different habitats exposed to high salinity through RNA-Seq analysis. Some candidate genes were further validated by qRT-PCR analysis. The observed increase in REC indicated that salinity caused harm to the seedlings throughout the duration of treatment. Proline content is an important indicator of physiological parameters in plants under stress (Mittal et al. 2012). Therefore, the content of free proline and REC were determined to investigate the effects of salt stress in the two varieties. The two varieties exhibited differences in proline content under salt stress, though the highest proline content was seen at 2 days for both. The change of proline content increased initially and then showed decrease, a trend which is generally observed in other species such as Gossypium hirsutum L. under stress (He et al. 2007).

RNA-Seq was performed to reveal changes in the transcriptomes of ‘Yunma 5’ and ‘Bamahuoma’ exposed to NaCl. As the scatter plots showed, ‘Bamahuoma’ exhibited more up-regulated and down-regulated genes than ‘Yunma 5’ during the salt stress stage. Both varieties had more up-regulated genes at 2 days. 4836 genes and 469 genes were differentially expressed at 2 days in ‘Bamahuoma’ and ‘Yunma 5’, respectively (Fig. 3 ). The trend of proline was the result of the regulation of these genes. A total of 220 genes were co-up-regulated in ‘Yunma 5’ and ‘Bamahuoma’. Among these, several salt-related genes were identified, indicating that there are overlaps at the transcriptional level between the two varieties in response to salt stress. These genes are involved in several mechanisms in plants under stress. In other studies, the genes of ABC transporter family members, UDP-glycosyltransferase proteins, ethylene response factors, heat shock proteins, alpha/beta-hydrolase superfamily proteins, and cysteine proteases were revealed to be salt-regulated in other species. These genes were found to have altered expression in two poplar species treated with NaCl (Zhang et al. 2014). We found that isoforms of heat shock protein were up-regulated in the two varieties at 2 days, a finding which was also reported previously in case of Petunia hybrida (Villarino et al. 2014). The alpha/beta-hydrolase superfamily of proteins catalyze proteolysis and play an essential role in allowing cells to survive under various stresses, including salt stress (Hilt and Wolf 1992). The papain family is the most well studied of the cysteine proteases that can be regulated by the plant hormone abscisic acid (ABA) induced by hydropenia. The expression of CYP15a, whose sequence is similar to cysteine proteases, was increased by more than two-fold in pea seedlings treated with NaCl and KCl (Jones and Mullet 1995). UDP-glucosyltransferase genes were up-regulated in both varieties. The stress-regulated UDP-glucosyltransferase gene UGT85U1 was shown to improve the salt tolerance of transgenic Arabidopsis plants (Ahrazem et al. 2015).

Based on searching in PlantTFDB 2.0, the DEGs co-expressed during salt stress in the two varieties had been clustered to different families, including MYB, GATA, NAC and HSF, that play important roles in the response to various stresses in plants (Singh et al. 2002; Shameer et al. 2009). MYB transcription factors have important functions in the stress response in industrial hemp. MYB transcription factors such as TaPIMPI positively regulate salt and disease resistance in wheat by coordinating regulation of stress-related genes involved in ABA and SA signaling pathways (Zhang et al. 2012). Two NAC genes (PK25206.1 and PK26157.1) were up-regulated in the two hemp varieties. NAC transcription factors were found to be involved in several signal transduction pathways in potato. Moreover, salt- and drought-related genes in Arabidopsis thaliana and rice are members of this family (Li et al. 2015; Hu et al. 2006). A GATA gene (PK07593.1) was up-regulated in the two hemp varieties and significantly up-regulated in ‘Bamahuoma’. ENA1, encoding a lithium and sodium ion transporter, is important to salt tolerance in yeast, and its expression is regulated by the rapamycin (TOR) pathway through the GATA transcription factors GLN3 and GAT1 (Crespo et al. 2001). A heat shock transcription factor (PK02428.1) was up-regulated in the two varieties and was the most significantly up-regulated expression profile in ‘Bamahuoma’ under salt stress. Twenty-five heat shock protein genes (OsHsf1-OsHsf25) were identified in rice and their expression is regulated by the abiotic stresses of salt and drought (Wan et al. 2010). Nine heat shock protein genes were identified from a proteomic analysis of rice, and 6 genes of them (OsHsp93.04, OsHsp71.10, OsHsp71.18, OsHsp72.57, OsHsp24.15 and OsHsp18.03) were up-regulated by salt stress (Ye et al. 2012). Moreover, the expression of the heat shock protein gene OsHsfB2b was strongly induced by heat, salt, abscisic acid (ABA), and polyethylene glycol (PEG) treatment and negatively regulated the response to salt and drought stress in rice (Xiang et al. 2013).

Different transporter genes were identified by searching against the transporter classification database (TCDB) and mostly clustered to ion, amino acid and glucose transmembrane transporters.

We applied STEM v1.3.8 to the genes with same expression patterns, and selected genes with expression pattern of first increase and then decrease after salt treatment for a more detailed functional analysis. These profiles (profile 16 in ‘Yunma 5’ and profile 14 in ‘Bamahuoma’) included 1714 ‘Yunma 5’ and 2509 ‘Bamahuoma’ differentially expressed genes. GO classification and KEGG enrichment were performed on these genes, revealing 13 DEGs in profile 16 and 15 DEGs in profile 14 that were enriched in amino acid metabolism. In addition, 17 DEGs in profile 14 in ‘Bamahuoma’ were enriched in the alpha-linolenic acid metabolism pathway and 12 in fatty acid metabolism. The accumulation of organic molecules is an example of an adaptation to stress. Small molecules such as amino acids and fatty acids can synthesize substances to keep the osmotic pressure in balance in plant cells. Salinity is a major stimulant for lipid production in microalgae, and an increase in NaCl content increased the production of lipids and unsaturated fatty acids in Chlamydomonas mexicana and Scenedesmus obliquus (Salama et al. 2013; Kaewkannetra et al. 2012). Fatty acid β-oxidation is a key step in lipid metabolism and hormone biosynthesis in plants, a key role that is played by acyl-CoA oxidase (Arent et al. 2008). Expression of five fatty acid genes in an Antarctic ice alga enhanced its adaption to high salinity (An et al. 2013). Furthermore, we identified aldehyde dehydrogenase family members, members of the fatty acid metabolism pathway. Stress can lead to the accumulation of toxic degradation products, including aldehydes (Srivastava et al. 2002). The overexpression of aldehyde dehydrogenase genes (ALDHs) from A. thaliana catalyzed the dehydrogenation of aldehydes and enhanced the salt tolerance of transgenic plants (Sunkar et al. 2003). Thus it is clear that in terms of the response of industrial hemp to salt stress, small molecule metabolism pathways deserve our attention. Finally, 33 DEGs in profile 16 were enriched in the spliceosome pathway. Under stress, plants can begin expressing stress-regulated genes through alternative splicing. Alternative splicing is an important method of gene expression regulation, directly determining the structure and function of diverse proteins (Kazan 2003).

Conclusions

We have presented here the first comprehensive transcriptome profiling analysis of Cannabis sativa under salt stress combined physiological parameters measurement. In this study, numerous genes encoding transcription factors and transporters showed different expression patterns between two varieties under stress. These results revealed that two industrial hemp varieties might have developed variety-specific adaptive mechanisms to salinity in their different habitats. To develop cultivars with high salt tolerance, especially bast fiber crops, the DEGs obtained in these two varieties can be further manipulated. Few studies have been performed on transcriptional profiling of Cannabis sativa under salt stress. The use of RNA-Seq and gene expression profiling to investigate the differences between two varieties of industrial hemp represent important novel aspects of our study. Our findings provide useful insights into the mechanisms of salt tolerance in fiber crops, particularly those grown in high-salinity soil.